XTX Markets
Research and engineering for data-driven electronic market making
Source confidence: Official + candidate reports + third-party guides · Last reviewed: 8 Sept 2026. Exact process varies by role, office, and year.
XTX Markets is an algorithmic trading firm whose official materials emphasize machine learning, large-scale data, and automated market making. Current role pages support separate quantitative-research and software-engineering preparation. Quantitative-research candidates report mathematics, machine-learning, and brainteaser questions, but their accounts cover specific roles and cycles. Third-party guides add broader context, and XTX does not publish one fixed interview sequence.
Interview Rounds
Interview processes vary by role, office, seniority, and year. We separate official company information from candidate reports and third-party guides.
Round 1:Role-specific openings and preparation boundary
Current XTX openings define distinct research and engineering skill profiles. Public official material does not prescribe a universal first-round format.
Round 2:Technical assessment or discussion (third-party)
Third-party guides describe mathematics, statistics, machine learning, coding, and engineering questions selected for the role. Exact stages and timing are not official.
Round 3:Machine-learning research interviews (reported)
One machine-learning researcher candidate reported neural networks, RNNs, transformers, time series, linear algebra, calculus, and basic mathematics. A London quantitative-research candidate in April 2023 reported linear models, simple neural networks, a brainteaser, and a later home assignment. These are role- and cycle-specific accounts.
Round 4:Later technical discussions (third-party)
Third-party guidance describes further role-relevant technical conversations. XTX does not publish this as a general interview stage, and the number and format can vary.
Focus Areas
Drill XTX's focus areas
Practice formats matched to how XTX interviews.
Estimation, inference, and regression questions as they come up in interviews.
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Free warm-ups in XTX's focus areas. No account required.
Your XTX prep path
The guide above is firm-wide. This checklist is role-specific where sourced.
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Suggested pace: about 7 days. This is a guide, not a firm-prescribed schedule. Every step below is tied to public sources for XTX.
Practice statistics, machine learning, and mathematics
Work through targeted problems and review every miss by topic before moving on.
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Supported by official sources plus candidate-reported details; exact formats can vary by role, office, and year.
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Upgrade to PremiumBased on official material, public candidate interview reports, and clearly labeled third-party guides; interview processes vary by role, office, and year. Last reviewed September 2026. Read more about how we source firm content. QuantReady is not affiliated with, endorsed by, or sponsored by XTX Markets. All company names and trademarks are the property of their respective owners.